code: def test_features_matching_loss_raises_exception(self):
      ft_matching_loss = FeatureMatchingLoss()
      length = random.randrange(1, 100_000)
      t1 = torch.randn(1, 2, length)
      t2 = torch.randn(1, 2, length + 1)
  
      with pytest.raises(AssertionError):
          ft_matching_loss([], [])
  
      with pytest.raises(AssertionError):
          ft_matching_loss([t1], [t1, t1])
  
      with pytest.raises(AssertionError):
          ft_matching_loss([t1], [t2])
  
file_path: audiocraft/tests/adversarial/test_losses.py
imports: import pytest
  import random
  import torch
  from audiocraft.adversarial import AdversarialLoss, get_adv_criterion, get_real_criterion, get_fake_criterion, FeatureMatchingLoss, MultiScaleDiscriminator
label_desc: Use image node_id 2 for calling the TestFeatureMatchingLoss obj's underlying member method code with example usage: obj.test_features_matching_loss_raises_exception() without return types